Experimental investigation into the feasibility of an extruded wing

Fabrications of extruded aluminum alloy structures are reviewed. The design criteria and the fabrication of the main structure of a sailplane wing made of a few extruded profiles longitudinally connected one to the other are illustrated. Structural tests recently carried out are reported upon

Multiple binding sites for transcriptional repressors can produce regular bursting and enhance noise suppression

Cells may control fluctuations in protein levels by means of negative autoregulation, where transcription factors bind DNA sites to repress their own production. Theoretical studies have assumed a single binding site for the repressor, while in most species it is found that multiple binding sites are arranged in clusters. We study a stochastic description of negative autoregulation with multiple binding sites for the repressor. We find that increasing the number of binding sites induces regular bursting of gene products. By tuning the threshold for repression, we show that multiple binding sites can also suppress fluctuations. Our results highlight possible roles for the presence of multiple binding sites of negative autoregulators

Associative memory on a small-world neural network

We study a model of associative memory based on a neural network with small-world structure. The efficacy of the network to retrieve one of the stored patterns exhibits a phase transition at a finite value of the disorder. The more ordered networks are unable to recover the patterns, and are always attracted to mixture states. Besides, for a range of the number of stored patterns, the efficacy has a maximum at an intermediate value of the disorder. We also give a statistical characterization of the attractors for all values of the disorder of the network.Comment: 5 pages, 4 figures (eps

Nonlinearity arising from noncooperative transcription factor binding enhances negative feedback and promotes genetic oscillations

We study the effects of multiple binding sites in the promoter of a genetic oscillator. We evaluate the regulatory function of a promoter with multiple binding sites in the absence of cooperative binding, and consider different hypotheses for how the number of bound repressors affects transcription rate. Effective Hill exponents of the resulting regulatory functions reveal an increase in the nonlinearity of the feedback with the number of binding sites. We identify optimal configurations that maximize the nonlinearity of the feedback. We use a generic model of a biochemical oscillator to show that this increased nonlinearity is reflected in enhanced oscillations, with larger amplitudes over wider oscillatory ranges. Although the study is motivated by genetic oscillations in the zebrafish segmentation clock, our findings may reveal a general principle for gene regulation.Comment: 11 pages, 8 figure

Synchronization in the presence of distributed delays

We study systems of identical coupled oscillators introducing a distribution of delay times in the coupling. For arbitrary network topologies, we show that the frequency and stability of the fully synchronized states depend only on the mean of the delay distribution. However, synchronization dynamics is sensitive to the shape of the distribution. In the presence of coupling delays, the synchronization rate can be maximal for a specific value of the coupling strength.Comment: 6 pages, 3 figure

A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available

Performance and genome-centric metagenomics of thermophilic single and two-stage anaerobic digesters treating cheese wastes

The present research is the first comprehensive study regarding the thermophilic anaerobic degradation of cheese wastewater, which combines the evaluation of different reactor configurations (i.e. single and two-stage continuous stirred tank reactors) on the process efficiency and the in-depth characterization of the microbial community structure using genome-centric metagenomics. Both reactor configurations showed acidification problems under the tested organic loading rates (OLRs) of 3.6 and 2.4 g COD/L-reactor day and the hydraulic retention time (HRT) of 15 days. However, the two-stage design reached a methane yield equal to 95% of the theoretical value, in contrast with the single stage configuration, which reached a maximum of 33% of the theoretical methane yield. The metagenomic analysis identified 22 new population genomes and revealed that the microbial compositions between the two configurations were remarkably different, demonstrating a higher methanogenic biodiversity in the two-stage configuration. In fact, the acidogenic reactor of the serial configuration was almost solely composed by the lactose degrader Bifidobacterium crudilactis UC0001. The predictive functional analyses of the main population genomes highlighted specific metabolic pathways responsible for the AD process and the mechanisms of main intermediates production. Particularly, the acetate accumulation experienced by the single stage configuration was mainly correlated to the low abundant syntrophic acetate oxidizer Tepidanaerobacter acetatoxydans UC0018 and to the absence of aceticlastic methanogens